Overview

Dataset statistics

Number of variables44
Number of observations40336
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.5 MiB
Average record size in memory352.0 B

Variable types

Numeric44

Alerts

PatientID is highly correlated with BaseExcess and 2 other fieldsHigh correlation
HR is highly correlated with O2Sat and 21 other fieldsHigh correlation
O2Sat is highly correlated with HR and 22 other fieldsHigh correlation
Temp is highly correlated with HR and 18 other fieldsHigh correlation
SBP is highly correlated with HR and 21 other fieldsHigh correlation
MAP is highly correlated with HR and 22 other fieldsHigh correlation
DBP is highly correlated with HR and 13 other fieldsHigh correlation
Resp is highly correlated with HR and 20 other fieldsHigh correlation
BaseExcess is highly correlated with PatientID and 7 other fieldsHigh correlation
HCO3 is highly correlated with PatientID and 6 other fieldsHigh correlation
FiO2 is highly correlated with BaseExcess and 6 other fieldsHigh correlation
pH is highly correlated with BaseExcess and 9 other fieldsHigh correlation
PaCO2 is highly correlated with BaseExcess and 7 other fieldsHigh correlation
SaO2 is highly correlated with BaseExcess and 4 other fieldsHigh correlation
AST is highly correlated with Alkalinephos and 1 other fieldsHigh correlation
BUN is highly correlated with HR and 23 other fieldsHigh correlation
Alkalinephos is highly correlated with AST and 1 other fieldsHigh correlation
Calcium is highly correlated with HR and 18 other fieldsHigh correlation
Chloride is highly correlated with PatientID and 12 other fieldsHigh correlation
Creatinine is highly correlated with HR and 22 other fieldsHigh correlation
Glucose is highly correlated with O2Sat and 9 other fieldsHigh correlation
Lactate is highly correlated with FiO2 and 4 other fieldsHigh correlation
Magnesium is highly correlated with HR and 21 other fieldsHigh correlation
Phosphate is highly correlated with BUN and 5 other fieldsHigh correlation
Potassium is highly correlated with HR and 26 other fieldsHigh correlation
Bilirubin_total is highly correlated with AST and 1 other fieldsHigh correlation
Hct is highly correlated with HR and 24 other fieldsHigh correlation
Hgb is highly correlated with HR and 21 other fieldsHigh correlation
PTT is highly correlated with HCO3 and 3 other fieldsHigh correlation
WBC is highly correlated with HR and 21 other fieldsHigh correlation
Platelets is highly correlated with HR and 23 other fieldsHigh correlation
Age is highly correlated with HR and 21 other fieldsHigh correlation
Gender is highly correlated with HR and 21 other fieldsHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
HospAdmTime is highly correlated with HR and 21 other fieldsHigh correlation
ICULOS is highly correlated with HR and 21 other fieldsHigh correlation
SepsisLabel is highly correlated with HR and 21 other fieldsHigh correlation
Sepsis is highly correlated with HR and 21 other fieldsHigh correlation
Hours is highly correlated with HR and 21 other fieldsHigh correlation
PatientID is highly correlated with HCO3 and 1 other fieldsHigh correlation
HR is highly correlated with O2Sat and 24 other fieldsHigh correlation
O2Sat is highly correlated with HR and 24 other fieldsHigh correlation
Temp is highly correlated with HR and 19 other fieldsHigh correlation
SBP is highly correlated with HR and 22 other fieldsHigh correlation
MAP is highly correlated with HR and 24 other fieldsHigh correlation
DBP is highly correlated with HR and 18 other fieldsHigh correlation
Resp is highly correlated with HR and 23 other fieldsHigh correlation
BaseExcess is highly correlated with HCO3 and 13 other fieldsHigh correlation
HCO3 is highly correlated with PatientID and 15 other fieldsHigh correlation
FiO2 is highly correlated with HR and 15 other fieldsHigh correlation
pH is highly correlated with BaseExcess and 14 other fieldsHigh correlation
PaCO2 is highly correlated with Temp and 16 other fieldsHigh correlation
SaO2 is highly correlated with BaseExcess and 6 other fieldsHigh correlation
AST is highly correlated with BUN and 6 other fieldsHigh correlation
BUN is highly correlated with HR and 30 other fieldsHigh correlation
Alkalinephos is highly correlated with AST and 6 other fieldsHigh correlation
Calcium is highly correlated with HR and 23 other fieldsHigh correlation
Chloride is highly correlated with PatientID and 16 other fieldsHigh correlation
Creatinine is highly correlated with HR and 30 other fieldsHigh correlation
Glucose is highly correlated with HR and 15 other fieldsHigh correlation
Lactate is highly correlated with BaseExcess and 12 other fieldsHigh correlation
Magnesium is highly correlated with HR and 28 other fieldsHigh correlation
Phosphate is highly correlated with HR and 23 other fieldsHigh correlation
Potassium is highly correlated with HR and 31 other fieldsHigh correlation
Bilirubin_total is highly correlated with AST and 3 other fieldsHigh correlation
Hct is highly correlated with HR and 27 other fieldsHigh correlation
Hgb is highly correlated with HR and 30 other fieldsHigh correlation
PTT is highly correlated with BaseExcess and 13 other fieldsHigh correlation
WBC is highly correlated with HR and 32 other fieldsHigh correlation
Fibrinogen is highly correlated with AST and 4 other fieldsHigh correlation
Platelets is highly correlated with HR and 31 other fieldsHigh correlation
Age is highly correlated with HR and 23 other fieldsHigh correlation
Gender is highly correlated with HR and 23 other fieldsHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
HospAdmTime is highly correlated with HR and 23 other fieldsHigh correlation
ICULOS is highly correlated with HR and 23 other fieldsHigh correlation
SepsisLabel is highly correlated with HR and 23 other fieldsHigh correlation
Sepsis is highly correlated with HR and 23 other fieldsHigh correlation
Hours is highly correlated with HR and 23 other fieldsHigh correlation
PatientID is highly correlated with HCO3 and 1 other fieldsHigh correlation
HR is highly correlated with O2Sat and 14 other fieldsHigh correlation
O2Sat is highly correlated with HR and 13 other fieldsHigh correlation
Temp is highly correlated with HR and 10 other fieldsHigh correlation
SBP is highly correlated with HR and 12 other fieldsHigh correlation
MAP is highly correlated with HR and 14 other fieldsHigh correlation
DBP is highly correlated with HR and 11 other fieldsHigh correlation
Resp is highly correlated with HR and 12 other fieldsHigh correlation
BaseExcess is highly correlated with HCO3 and 4 other fieldsHigh correlation
HCO3 is highly correlated with PatientID and 3 other fieldsHigh correlation
FiO2 is highly correlated with BaseExcess and 4 other fieldsHigh correlation
pH is highly correlated with BaseExcess and 4 other fieldsHigh correlation
PaCO2 is highly correlated with BaseExcess and 4 other fieldsHigh correlation
SaO2 is highly correlated with FiO2 and 2 other fieldsHigh correlation
AST is highly correlated with Alkalinephos and 1 other fieldsHigh correlation
BUN is highly correlated with Calcium and 9 other fieldsHigh correlation
Alkalinephos is highly correlated with AST and 1 other fieldsHigh correlation
Calcium is highly correlated with BUN and 5 other fieldsHigh correlation
Chloride is highly correlated with PatientID and 4 other fieldsHigh correlation
Creatinine is highly correlated with HR and 19 other fieldsHigh correlation
Lactate is highly correlated with FiO2 and 2 other fieldsHigh correlation
Magnesium is highly correlated with BUN and 8 other fieldsHigh correlation
Phosphate is highly correlated with BUN and 3 other fieldsHigh correlation
Potassium is highly correlated with BUN and 7 other fieldsHigh correlation
Bilirubin_total is highly correlated with AST and 1 other fieldsHigh correlation
Hct is highly correlated with BUN and 6 other fieldsHigh correlation
Hgb is highly correlated with BUN and 6 other fieldsHigh correlation
PTT is highly correlated with HCO3 and 1 other fieldsHigh correlation
WBC is highly correlated with BUN and 6 other fieldsHigh correlation
Platelets is highly correlated with HR and 9 other fieldsHigh correlation
Age is highly correlated with HR and 13 other fieldsHigh correlation
Gender is highly correlated with HR and 13 other fieldsHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
HospAdmTime is highly correlated with HR and 13 other fieldsHigh correlation
ICULOS is highly correlated with HR and 13 other fieldsHigh correlation
SepsisLabel is highly correlated with HR and 13 other fieldsHigh correlation
Sepsis is highly correlated with HR and 13 other fieldsHigh correlation
Hours is highly correlated with HR and 13 other fieldsHigh correlation
PatientID has unique values Unique
DBP has 7411 (18.4%) zeros Zeros
EtCO2 has 37120 (92.0%) zeros Zeros
BaseExcess has 27126 (67.3%) zeros Zeros
HCO3 has 20119 (49.9%) zeros Zeros
FiO2 has 22527 (55.8%) zeros Zeros
pH has 21401 (53.1%) zeros Zeros
PaCO2 has 21980 (54.5%) zeros Zeros
SaO2 has 27248 (67.6%) zeros Zeros
AST has 25979 (64.4%) zeros Zeros
BUN has 2018 (5.0%) zeros Zeros
Alkalinephos has 26163 (64.9%) zeros Zeros
Calcium has 5339 (13.2%) zeros Zeros
Chloride has 18925 (46.9%) zeros Zeros
Creatinine has 2049 (5.1%) zeros Zeros
Bilirubin_direct has 38279 (94.9%) zeros Zeros
Glucose has 1580 (3.9%) zeros Zeros
Lactate has 27843 (69.0%) zeros Zeros
Magnesium has 4931 (12.2%) zeros Zeros
Phosphate has 12015 (29.8%) zeros Zeros
Potassium has 1867 (4.6%) zeros Zeros
Bilirubin_total has 26088 (64.7%) zeros Zeros
TroponinI has 33283 (82.5%) zeros Zeros
Hct has 2317 (5.7%) zeros Zeros
Hgb has 2448 (6.1%) zeros Zeros
PTT has 20098 (49.8%) zeros Zeros
WBC has 2625 (6.5%) zeros Zeros
Fibrinogen has 35821 (88.8%) zeros Zeros
Platelets has 2577 (6.4%) zeros Zeros
Unit1 has 15617 (38.7%) zeros Zeros
Unit2 has 15617 (38.7%) zeros Zeros

Reproduction

Analysis started2021-11-29 10:26:14.731382
Analysis finished2021-11-29 10:26:32.574625
Duration17.84 seconds
Software versionpandas-profiling v3.1.1
Download configurationconfig.json

Variables

PatientID
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct40336
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59671.27286
Minimum1
Maximum120000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:32.618944image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2017.75
Q110084.75
median20475.5
Q3109916.25
95-th percentile117983.25
Maximum120000
Range119999
Interquartile range (IQR)99831.5

Descriptive statistics

Standard deviation50251.33712
Coefficient of variation (CV)0.842136169
Kurtosis-1.946653503
Mean59671.27286
Median Absolute Deviation (MAD)20307
Skewness0.01560297418
Sum2406900462
Variance2525196883
MonotonicityStrictly increasing
2021-11-29T11:26:32.722318image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11
 
< 0.1%
1065591
 
< 0.1%
1065521
 
< 0.1%
1065531
 
< 0.1%
1065541
 
< 0.1%
1065551
 
< 0.1%
1065561
 
< 0.1%
1065571
 
< 0.1%
1065581
 
< 0.1%
1065601
 
< 0.1%
Other values (40326)40326
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
51
< 0.1%
61
< 0.1%
71
< 0.1%
81
< 0.1%
91
< 0.1%
101
< 0.1%
ValueCountFrequency (%)
1200001
< 0.1%
1199991
< 0.1%
1199981
< 0.1%
1199971
< 0.1%
1199961
< 0.1%
1199951
< 0.1%
1199941
< 0.1%
1199931
< 0.1%
1199921
< 0.1%
1199911
< 0.1%

HR
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct266
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.67897164
Minimum0
Maximum333
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:32.824350image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q121
median35
Q343
95-th percentile55
Maximum333
Range333
Interquartile range (IQR)22

Descriptive statistics

Standard deviation22.09661892
Coefficient of variation (CV)0.6371763025
Kurtosis38.58764829
Mean34.67897164
Median Absolute Deviation (MAD)11
Skewness4.51879553
Sum1398811
Variance488.2605678
MonotonicityNot monotonic
2021-11-29T11:26:32.920928image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
351308
 
3.2%
381248
 
3.1%
361229
 
3.0%
371215
 
3.0%
391208
 
3.0%
401155
 
2.9%
421113
 
2.8%
411106
 
2.7%
341054
 
2.6%
44998
 
2.5%
Other values (256)28702
71.2%
ValueCountFrequency (%)
05
 
< 0.1%
112
 
< 0.1%
246
 
0.1%
3127
 
0.3%
4219
0.5%
5221
0.5%
6234
0.6%
7377
0.9%
8328
0.8%
9329
0.8%
ValueCountFrequency (%)
3331
 
< 0.1%
3284
< 0.1%
3241
 
< 0.1%
3211
 
< 0.1%
3181
 
< 0.1%
3121
 
< 0.1%
3112
< 0.1%
3101
 
< 0.1%
3081
 
< 0.1%
3071
 
< 0.1%

O2Sat
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct266
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.4558211
Minimum0
Maximum331
Zeros18
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:33.023016image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q120
median33
Q342
95-th percentile54
Maximum331
Range331
Interquartile range (IQR)22

Descriptive statistics

Standard deviation21.96750436
Coefficient of variation (CV)0.6566123213
Kurtosis37.39321777
Mean33.4558211
Median Absolute Deviation (MAD)11
Skewness4.421361261
Sum1349474
Variance482.5712476
MonotonicityNot monotonic
2021-11-29T11:26:33.118731image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
351249
 
3.1%
361198
 
3.0%
391170
 
2.9%
381145
 
2.8%
371126
 
2.8%
401103
 
2.7%
421059
 
2.6%
411053
 
2.6%
341035
 
2.6%
191012
 
2.5%
Other values (256)29186
72.4%
ValueCountFrequency (%)
018
 
< 0.1%
122
 
0.1%
284
 
0.2%
3179
0.4%
4257
0.6%
5288
0.7%
6278
0.7%
7428
1.1%
8397
1.0%
9417
1.0%
ValueCountFrequency (%)
3311
< 0.1%
3282
< 0.1%
3271
< 0.1%
3251
< 0.1%
3232
< 0.1%
3181
< 0.1%
3122
< 0.1%
3101
< 0.1%
3082
< 0.1%
3041
< 0.1%

Temp
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct155
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.02127132
Minimum0
Maximum282
Zeros284
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:33.291898image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q16
median10
Q315
95-th percentile37
Maximum282
Range282
Interquartile range (IQR)9

Descriptive statistics

Standard deviation12.29054059
Coefficient of variation (CV)0.9438817679
Kurtosis38.28440192
Mean13.02127132
Median Absolute Deviation (MAD)4
Skewness4.26450895
Sum525226
Variance151.0573881
MonotonicityNot monotonic
2021-11-29T11:26:33.385298image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
92989
 
7.4%
102904
 
7.2%
112701
 
6.7%
52664
 
6.6%
82548
 
6.3%
42503
 
6.2%
72388
 
5.9%
62385
 
5.9%
122197
 
5.4%
131804
 
4.5%
Other values (145)15253
37.8%
ValueCountFrequency (%)
0284
 
0.7%
1469
 
1.2%
21019
 
2.5%
31761
4.4%
42503
6.2%
52664
6.6%
62385
5.9%
72388
5.9%
82548
6.3%
92989
7.4%
ValueCountFrequency (%)
2821
< 0.1%
2161
< 0.1%
2141
< 0.1%
2131
< 0.1%
2061
< 0.1%
2051
< 0.1%
1962
< 0.1%
1951
< 0.1%
1941
< 0.1%
1801
< 0.1%

SBP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct269
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.87249603
Minimum0
Maximum332
Zeros282
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:33.487344image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8
Q119
median33
Q342
95-th percentile54
Maximum332
Range332
Interquartile range (IQR)23

Descriptive statistics

Standard deviation21.84777976
Coefficient of variation (CV)0.6646218691
Kurtosis37.74020191
Mean32.87249603
Median Absolute Deviation (MAD)11
Skewness4.380467097
Sum1325945
Variance477.3254803
MonotonicityNot monotonic
2021-11-29T11:26:33.582543image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
351247
 
3.1%
371197
 
3.0%
361163
 
2.9%
381155
 
2.9%
391100
 
2.7%
191082
 
2.7%
341058
 
2.6%
181056
 
2.6%
211051
 
2.6%
401045
 
2.6%
Other values (259)29182
72.3%
ValueCountFrequency (%)
0282
0.7%
174
 
0.2%
293
 
0.2%
3199
0.5%
4273
0.7%
5274
0.7%
6246
0.6%
7410
1.0%
8381
0.9%
9384
1.0%
ValueCountFrequency (%)
3321
< 0.1%
3301
< 0.1%
3261
< 0.1%
3251
< 0.1%
3221
< 0.1%
3211
< 0.1%
3161
< 0.1%
3121
< 0.1%
3111
< 0.1%
3101
< 0.1%

MAP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct267
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.6904998
Minimum0
Maximum332
Zeros104
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:33.684603image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q120
median34
Q343
95-th percentile55
Maximum332
Range332
Interquartile range (IQR)23

Descriptive statistics

Standard deviation22.03633825
Coefficient of variation (CV)0.6540816662
Kurtosis37.64697766
Mean33.6904998
Median Absolute Deviation (MAD)11
Skewness4.429640001
Sum1358940
Variance485.6002033
MonotonicityNot monotonic
2021-11-29T11:26:33.780370image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
351308
 
3.2%
371250
 
3.1%
361201
 
3.0%
381186
 
2.9%
391120
 
2.8%
401099
 
2.7%
411053
 
2.6%
421050
 
2.6%
341049
 
2.6%
191009
 
2.5%
Other values (257)29011
71.9%
ValueCountFrequency (%)
0104
 
0.3%
1126
 
0.3%
2166
0.4%
3212
0.5%
4218
0.5%
5207
0.5%
6216
0.5%
7411
1.0%
8348
0.9%
9349
0.9%
ValueCountFrequency (%)
3321
< 0.1%
3291
< 0.1%
3281
< 0.1%
3261
< 0.1%
3241
< 0.1%
3221
< 0.1%
3191
< 0.1%
3112
< 0.1%
3091
< 0.1%
3081
< 0.1%

DBP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct260
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.4194764
Minimum0
Maximum332
Zeros7411
Zeros (%)18.4%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:33.882739image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110
median24
Q339
95-th percentile53
Maximum332
Range332
Interquartile range (IQR)29

Descriptive statistics

Standard deviation23.87475816
Coefficient of variation (CV)0.9036802169
Kurtosis24.59758864
Mean26.4194764
Median Absolute Deviation (MAD)15
Skewness3.204315792
Sum1065656
Variance570.0040773
MonotonicityNot monotonic
2021-11-29T11:26:33.974453image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
07411
 
18.4%
21951
 
2.4%
35946
 
2.3%
20940
 
2.3%
19932
 
2.3%
37932
 
2.3%
38917
 
2.3%
36910
 
2.3%
39902
 
2.2%
18881
 
2.2%
Other values (250)24614
61.0%
ValueCountFrequency (%)
07411
18.4%
1191
 
0.5%
2188
 
0.5%
3268
 
0.7%
4319
 
0.8%
5302
 
0.7%
6242
 
0.6%
7374
 
0.9%
8333
 
0.8%
9328
 
0.8%
ValueCountFrequency (%)
3321
< 0.1%
3261
< 0.1%
3251
< 0.1%
3221
< 0.1%
3161
< 0.1%
3131
< 0.1%
3121
< 0.1%
3111
< 0.1%
3081
< 0.1%
3061
< 0.1%

Resp
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct262
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.57325962
Minimum0
Maximum327
Zeros71
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:34.072380image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8
Q119
median32
Q341
95-th percentile54
Maximum327
Range327
Interquartile range (IQR)22

Descriptive statistics

Standard deviation21.40425304
Coefficient of variation (CV)0.6571111793
Kurtosis36.79536374
Mean32.57325962
Median Absolute Deviation (MAD)11
Skewness4.341771675
Sum1313875
Variance458.1420483
MonotonicityNot monotonic
2021-11-29T11:26:34.169166image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
351229
 
3.0%
371173
 
2.9%
381167
 
2.9%
361150
 
2.9%
391086
 
2.7%
401061
 
2.6%
411037
 
2.6%
341037
 
2.6%
191012
 
2.5%
331010
 
2.5%
Other values (252)29374
72.8%
ValueCountFrequency (%)
071
 
0.2%
165
 
0.2%
289
 
0.2%
3221
0.5%
4300
0.7%
5310
0.8%
6304
0.8%
7413
1.0%
8409
1.0%
9428
1.1%
ValueCountFrequency (%)
3271
< 0.1%
3231
< 0.1%
3211
< 0.1%
3151
< 0.1%
3131
< 0.1%
3092
< 0.1%
3022
< 0.1%
3001
< 0.1%
2982
< 0.1%
2972
< 0.1%

EtCO2
Real number (ℝ≥0)

ZEROS

Distinct130
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.428897263
Minimum0
Maximum308
Zeros37120
Zeros (%)92.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:34.271635image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum308
Range308
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.557861422
Coefficient of variation (CV)5.989136969
Kurtosis299.6242785
Mean1.428897263
Median Absolute Deviation (MAD)0
Skewness13.8235408
Sum57636
Variance73.23699212
MonotonicityNot monotonic
2021-11-29T11:26:34.368008image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
037120
92.0%
2284
 
0.7%
1231
 
0.6%
3221
 
0.5%
4178
 
0.4%
6154
 
0.4%
5143
 
0.4%
7122
 
0.3%
897
 
0.2%
1193
 
0.2%
Other values (120)1693
 
4.2%
ValueCountFrequency (%)
037120
92.0%
1231
 
0.6%
2284
 
0.7%
3221
 
0.5%
4178
 
0.4%
5143
 
0.4%
6154
 
0.4%
7122
 
0.3%
897
 
0.2%
975
 
0.2%
ValueCountFrequency (%)
3081
< 0.1%
2931
< 0.1%
2871
< 0.1%
2551
< 0.1%
2461
< 0.1%
2381
< 0.1%
2251
< 0.1%
2221
< 0.1%
2201
< 0.1%
2171
< 0.1%

BaseExcess
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct66
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.086101745
Minimum0
Maximum112
Zeros27126
Zeros (%)67.3%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:34.472675image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile11
Maximum112
Range112
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.621227635
Coefficient of variation (CV)2.215245563
Kurtosis46.74251388
Mean2.086101745
Median Absolute Deviation (MAD)0
Skewness4.761833485
Sum84145
Variance21.35574485
MonotonicityNot monotonic
2021-11-29T11:26:34.566692image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
027126
67.3%
11941
 
4.8%
21585
 
3.9%
41388
 
3.4%
31302
 
3.2%
51192
 
3.0%
61038
 
2.6%
7811
 
2.0%
8769
 
1.9%
9574
 
1.4%
Other values (56)2610
 
6.5%
ValueCountFrequency (%)
027126
67.3%
11941
 
4.8%
21585
 
3.9%
31302
 
3.2%
41388
 
3.4%
51192
 
3.0%
61038
 
2.6%
7811
 
2.0%
8769
 
1.9%
9574
 
1.4%
ValueCountFrequency (%)
1121
< 0.1%
1041
< 0.1%
901
< 0.1%
851
< 0.1%
821
< 0.1%
811
< 0.1%
701
< 0.1%
681
< 0.1%
661
< 0.1%
652
< 0.1%

HCO3
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct43
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.612157874
Minimum0
Maximum85
Zeros20119
Zeros (%)49.9%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:34.737734image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile6
Maximum85
Range85
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.559540631
Coefficient of variation (CV)1.587648873
Kurtosis59.74813623
Mean1.612157874
Median Absolute Deviation (MAD)1
Skewness4.684876614
Sum65028
Variance6.55124824
MonotonicityNot monotonic
2021-11-29T11:26:34.824997image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
020119
49.9%
26154
 
15.3%
34118
 
10.2%
14012
 
9.9%
42363
 
5.9%
51069
 
2.7%
6973
 
2.4%
8411
 
1.0%
7363
 
0.9%
9177
 
0.4%
Other values (33)577
 
1.4%
ValueCountFrequency (%)
020119
49.9%
14012
 
9.9%
26154
 
15.3%
34118
 
10.2%
42363
 
5.9%
51069
 
2.7%
6973
 
2.4%
7363
 
0.9%
8411
 
1.0%
9177
 
0.4%
ValueCountFrequency (%)
851
 
< 0.1%
491
 
< 0.1%
451
 
< 0.1%
431
 
< 0.1%
422
< 0.1%
391
 
< 0.1%
372
< 0.1%
363
< 0.1%
352
< 0.1%
331
 
< 0.1%

FiO2
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct92
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.207184649
Minimum0
Maximum133
Zeros22527
Zeros (%)55.8%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:34.917343image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile15
Maximum133
Range133
Interquartile range (IQR)4

Descriptive statistics

Standard deviation6.446987159
Coefficient of variation (CV)2.010170247
Kurtosis40.79745152
Mean3.207184649
Median Absolute Deviation (MAD)0
Skewness4.698529699
Sum129365
Variance41.56364343
MonotonicityNot monotonic
2021-11-29T11:26:35.017141image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
022527
55.8%
13240
 
8.0%
21964
 
4.9%
31759
 
4.4%
41475
 
3.7%
51198
 
3.0%
61062
 
2.6%
7885
 
2.2%
8775
 
1.9%
9676
 
1.7%
Other values (82)4775
 
11.8%
ValueCountFrequency (%)
022527
55.8%
13240
 
8.0%
21964
 
4.9%
31759
 
4.4%
41475
 
3.7%
51198
 
3.0%
61062
 
2.6%
7885
 
2.2%
8775
 
1.9%
9676
 
1.7%
ValueCountFrequency (%)
1331
< 0.1%
1161
< 0.1%
1121
< 0.1%
1111
< 0.1%
961
< 0.1%
921
< 0.1%
902
< 0.1%
892
< 0.1%
871
< 0.1%
861
< 0.1%

pH
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct72
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.666922848
Minimum0
Maximum124
Zeros21401
Zeros (%)53.1%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:35.115641image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile12
Maximum124
Range124
Interquartile range (IQR)4

Descriptive statistics

Standard deviation5.000736548
Coefficient of variation (CV)1.875096069
Kurtosis41.66933357
Mean2.666922848
Median Absolute Deviation (MAD)0
Skewness4.375676046
Sum107573
Variance25.00736602
MonotonicityNot monotonic
2021-11-29T11:26:35.215900image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
021401
53.1%
14447
 
11.0%
22579
 
6.4%
31715
 
4.3%
41601
 
4.0%
51358
 
3.4%
61220
 
3.0%
71012
 
2.5%
8941
 
2.3%
9719
 
1.8%
Other values (62)3343
 
8.3%
ValueCountFrequency (%)
021401
53.1%
14447
 
11.0%
22579
 
6.4%
31715
 
4.3%
41601
 
4.0%
51358
 
3.4%
61220
 
3.0%
71012
 
2.5%
8941
 
2.3%
9719
 
1.8%
ValueCountFrequency (%)
1241
< 0.1%
1101
< 0.1%
921
< 0.1%
861
< 0.1%
841
< 0.1%
821
< 0.1%
741
< 0.1%
701
< 0.1%
681
< 0.1%
661
< 0.1%

PaCO2
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct56
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.139552757
Minimum0
Maximum112
Zeros21980
Zeros (%)54.5%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:35.316473image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile10
Maximum112
Range112
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.005417979
Coefficient of variation (CV)1.872081895
Kurtosis43.28526748
Mean2.139552757
Median Absolute Deviation (MAD)0
Skewness4.342797685
Sum86301
Variance16.04337319
MonotonicityNot monotonic
2021-11-29T11:26:35.411210image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
021980
54.5%
14651
 
11.5%
22897
 
7.2%
32162
 
5.4%
41732
 
4.3%
51434
 
3.6%
61088
 
2.7%
7943
 
2.3%
8737
 
1.8%
9621
 
1.5%
Other values (46)2091
 
5.2%
ValueCountFrequency (%)
021980
54.5%
14651
 
11.5%
22897
 
7.2%
32162
 
5.4%
41732
 
4.3%
51434
 
3.6%
61088
 
2.7%
7943
 
2.3%
8737
 
1.8%
9621
 
1.5%
ValueCountFrequency (%)
1121
< 0.1%
831
< 0.1%
821
< 0.1%
641
< 0.1%
582
< 0.1%
542
< 0.1%
521
< 0.1%
501
< 0.1%
491
< 0.1%
482
< 0.1%

SaO2
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct53
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.327870885
Minimum0
Maximum89
Zeros27248
Zeros (%)67.6%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:35.511567image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile7
Maximum89
Range89
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.21999805
Coefficient of variation (CV)2.424933092
Kurtosis70.31673725
Mean1.327870885
Median Absolute Deviation (MAD)0
Skewness5.822948902
Sum53561
Variance10.36838744
MonotonicityNot monotonic
2021-11-29T11:26:35.604097image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
027248
67.6%
14034
 
10.0%
22428
 
6.0%
31417
 
3.5%
41280
 
3.2%
5859
 
2.1%
6705
 
1.7%
7494
 
1.2%
8375
 
0.9%
9300
 
0.7%
Other values (43)1196
 
3.0%
ValueCountFrequency (%)
027248
67.6%
14034
 
10.0%
22428
 
6.0%
31417
 
3.5%
41280
 
3.2%
5859
 
2.1%
6705
 
1.7%
7494
 
1.2%
8375
 
0.9%
9300
 
0.7%
ValueCountFrequency (%)
891
< 0.1%
831
< 0.1%
681
< 0.1%
641
< 0.1%
631
< 0.1%
601
< 0.1%
582
< 0.1%
561
< 0.1%
551
< 0.1%
501
< 0.1%

AST
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct27
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6243306228
Minimum0
Maximum71
Zeros25979
Zeros (%)64.4%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:35.691477image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum71
Range71
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.295532864
Coefficient of variation (CV)2.075074996
Kurtosis268.1563188
Mean0.6243306228
Median Absolute Deviation (MAD)0
Skewness8.810777053
Sum25183
Variance1.678405403
MonotonicityNot monotonic
2021-11-29T11:26:35.772042image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
025979
64.4%
18712
 
21.6%
23570
 
8.9%
3985
 
2.4%
4507
 
1.3%
5187
 
0.5%
6158
 
0.4%
764
 
0.2%
850
 
0.1%
926
 
0.1%
Other values (17)98
 
0.2%
ValueCountFrequency (%)
025979
64.4%
18712
 
21.6%
23570
 
8.9%
3985
 
2.4%
4507
 
1.3%
5187
 
0.5%
6158
 
0.4%
764
 
0.2%
850
 
0.1%
926
 
0.1%
ValueCountFrequency (%)
711
< 0.1%
302
< 0.1%
261
< 0.1%
251
< 0.1%
232
< 0.1%
222
< 0.1%
212
< 0.1%
202
< 0.1%
181
< 0.1%
172
< 0.1%

BUN
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct45
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.64200714
Minimum0
Maximum79
Zeros2018
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:35.868148image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile6
Maximum79
Range79
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.401502479
Coefficient of variation (CV)0.9089689589
Kurtosis62.42669265
Mean2.64200714
Median Absolute Deviation (MAD)1
Skewness5.013111263
Sum106568
Variance5.767214159
MonotonicityNot monotonic
2021-11-29T11:26:35.964725image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
212804
31.7%
19921
24.6%
37349
18.2%
43555
 
8.8%
02018
 
5.0%
51508
 
3.7%
61193
 
3.0%
7525
 
1.3%
8503
 
1.2%
9233
 
0.6%
Other values (35)727
 
1.8%
ValueCountFrequency (%)
02018
 
5.0%
19921
24.6%
212804
31.7%
37349
18.2%
43555
 
8.8%
51508
 
3.7%
61193
 
3.0%
7525
 
1.3%
8503
 
1.2%
9233
 
0.6%
ValueCountFrequency (%)
791
< 0.1%
471
< 0.1%
451
< 0.1%
441
< 0.1%
421
< 0.1%
401
< 0.1%
391
< 0.1%
382
< 0.1%
371
< 0.1%
361
< 0.1%

Alkalinephos
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct28
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6183310194
Minimum0
Maximum69
Zeros26163
Zeros (%)64.9%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:36.132421image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum69
Range69
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.299952856
Coefficient of variation (CV)2.1023575
Kurtosis248.1361222
Mean0.6183310194
Median Absolute Deviation (MAD)0
Skewness8.692388444
Sum24941
Variance1.689877428
MonotonicityNot monotonic
2021-11-29T11:26:36.214058image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
026163
64.9%
18602
 
21.3%
23504
 
8.7%
3976
 
2.4%
4511
 
1.3%
5184
 
0.5%
6154
 
0.4%
770
 
0.2%
847
 
0.1%
924
 
0.1%
Other values (18)101
 
0.3%
ValueCountFrequency (%)
026163
64.9%
18602
 
21.3%
23504
 
8.7%
3976
 
2.4%
4511
 
1.3%
5184
 
0.5%
6154
 
0.4%
770
 
0.2%
847
 
0.1%
924
 
0.1%
ValueCountFrequency (%)
691
< 0.1%
311
< 0.1%
302
< 0.1%
261
< 0.1%
251
< 0.1%
232
< 0.1%
222
< 0.1%
211
< 0.1%
202
< 0.1%
182
< 0.1%

Calcium
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct49
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.264255256
Minimum0
Maximum67
Zeros5339
Zeros (%)13.2%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:36.311136image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile6
Maximum67
Range67
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.430092647
Coefficient of variation (CV)1.073241473
Kurtosis78.2375506
Mean2.264255256
Median Absolute Deviation (MAD)1
Skewness5.787450112
Sum91331
Variance5.905350272
MonotonicityNot monotonic
2021-11-29T11:26:36.407894image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
211211
27.8%
111194
27.8%
36122
15.2%
05339
13.2%
42674
 
6.6%
51337
 
3.3%
6782
 
1.9%
7504
 
1.2%
8328
 
0.8%
9206
 
0.5%
Other values (39)639
 
1.6%
ValueCountFrequency (%)
05339
13.2%
111194
27.8%
211211
27.8%
36122
15.2%
42674
 
6.6%
51337
 
3.3%
6782
 
1.9%
7504
 
1.2%
8328
 
0.8%
9206
 
0.5%
ValueCountFrequency (%)
671
< 0.1%
621
< 0.1%
581
< 0.1%
521
< 0.1%
502
< 0.1%
482
< 0.1%
471
< 0.1%
441
< 0.1%
411
< 0.1%
391
< 0.1%

Chloride
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct44
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.746975407
Minimum0
Maximum76
Zeros18925
Zeros (%)46.9%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:36.509060image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile6
Maximum76
Range76
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.75545879
Coefficient of variation (CV)1.577273944
Kurtosis47.79636987
Mean1.746975407
Median Absolute Deviation (MAD)1
Skewness4.549743988
Sum70466
Variance7.592553142
MonotonicityNot monotonic
2021-11-29T11:26:36.597365image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
018925
46.9%
26288
 
15.6%
14641
 
11.5%
34055
 
10.1%
42348
 
5.8%
51156
 
2.9%
61019
 
2.5%
8474
 
1.2%
7449
 
1.1%
9225
 
0.6%
Other values (34)756
 
1.9%
ValueCountFrequency (%)
018925
46.9%
14641
 
11.5%
26288
 
15.6%
34055
 
10.1%
42348
 
5.8%
51156
 
2.9%
61019
 
2.5%
7449
 
1.1%
8474
 
1.2%
9225
 
0.6%
ValueCountFrequency (%)
761
 
< 0.1%
481
 
< 0.1%
471
 
< 0.1%
452
 
< 0.1%
442
 
< 0.1%
426
< 0.1%
401
 
< 0.1%
391
 
< 0.1%
381
 
< 0.1%
374
< 0.1%

Creatinine
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct30
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.345696152
Minimum0
Maximum79
Zeros2049
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:36.688341image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum79
Range79
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.890740736
Coefficient of variation (CV)0.8060467396
Kurtosis88.98225287
Mean2.345696152
Median Absolute Deviation (MAD)1
Skewness4.942139008
Sum94616
Variance3.574900529
MonotonicityNot monotonic
2021-11-29T11:26:36.770736image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
213444
33.3%
111014
27.3%
37727
19.2%
43055
 
7.6%
02049
 
5.1%
51297
 
3.2%
6613
 
1.5%
7367
 
0.9%
8204
 
0.5%
9148
 
0.4%
Other values (20)418
 
1.0%
ValueCountFrequency (%)
02049
 
5.1%
111014
27.3%
213444
33.3%
37727
19.2%
43055
 
7.6%
51297
 
3.2%
6613
 
1.5%
7367
 
0.9%
8204
 
0.5%
9148
 
0.4%
ValueCountFrequency (%)
791
 
< 0.1%
321
 
< 0.1%
272
 
< 0.1%
262
 
< 0.1%
251
 
< 0.1%
244
< 0.1%
234
< 0.1%
225
< 0.1%
215
< 0.1%
207
< 0.1%

Bilirubin_direct
Real number (ℝ≥0)

ZEROS

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07412733042
Minimum0
Maximum13
Zeros38279
Zeros (%)94.9%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:36.849914image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4115103319
Coefficient of variation (CV)5.551398243
Kurtosis178.3339449
Mean0.07412733042
Median Absolute Deviation (MAD)0
Skewness10.62561942
Sum2990
Variance0.1693407532
MonotonicityNot monotonic
2021-11-29T11:26:36.927507image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
038279
94.9%
11568
 
3.9%
2304
 
0.8%
379
 
0.2%
451
 
0.1%
517
 
< 0.1%
616
 
< 0.1%
810
 
< 0.1%
75
 
< 0.1%
103
 
< 0.1%
Other values (3)4
 
< 0.1%
ValueCountFrequency (%)
038279
94.9%
11568
 
3.9%
2304
 
0.8%
379
 
0.2%
451
 
0.1%
517
 
< 0.1%
616
 
< 0.1%
75
 
< 0.1%
810
 
< 0.1%
103
 
< 0.1%
ValueCountFrequency (%)
131
 
< 0.1%
121
 
< 0.1%
112
 
< 0.1%
103
 
< 0.1%
810
 
< 0.1%
75
 
< 0.1%
616
 
< 0.1%
517
 
< 0.1%
451
0.1%
379
0.2%

Glucose
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct101
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.582606109
Minimum0
Maximum154
Zeros1580
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:37.018441image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q39
95-th percentile21
Maximum154
Range154
Interquartile range (IQR)7

Descriptive statistics

Standard deviation7.641244288
Coefficient of variation (CV)1.160823565
Kurtosis38.89265385
Mean6.582606109
Median Absolute Deviation (MAD)3
Skewness4.149236373
Sum265516
Variance58.38861427
MonotonicityNot monotonic
2021-11-29T11:26:37.116707image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26506
16.1%
15429
13.5%
34738
11.7%
43508
 
8.7%
52605
 
6.5%
62059
 
5.1%
71815
 
4.5%
81596
 
4.0%
01580
 
3.9%
91498
 
3.7%
Other values (91)9002
22.3%
ValueCountFrequency (%)
01580
 
3.9%
15429
13.5%
26506
16.1%
34738
11.7%
43508
8.7%
52605
6.5%
62059
 
5.1%
71815
 
4.5%
81596
 
4.0%
91498
 
3.7%
ValueCountFrequency (%)
1541
< 0.1%
1511
< 0.1%
1472
< 0.1%
1441
< 0.1%
1401
< 0.1%
1281
< 0.1%
1241
< 0.1%
1221
< 0.1%
1191
< 0.1%
1161
< 0.1%

Lactate
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct46
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.027518842
Minimum0
Maximum63
Zeros27843
Zeros (%)69.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:37.219980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum63
Range63
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.65426701
Coefficient of variation (CV)2.583180865
Kurtosis67.63020111
Mean1.027518842
Median Absolute Deviation (MAD)0
Skewness6.195106397
Sum41446
Variance7.04513336
MonotonicityNot monotonic
2021-11-29T11:26:37.310776image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
027843
69.0%
14783
 
11.9%
22690
 
6.7%
31373
 
3.4%
41045
 
2.6%
5573
 
1.4%
6521
 
1.3%
7347
 
0.9%
8286
 
0.7%
10165
 
0.4%
Other values (36)710
 
1.8%
ValueCountFrequency (%)
027843
69.0%
14783
 
11.9%
22690
 
6.7%
31373
 
3.4%
41045
 
2.6%
5573
 
1.4%
6521
 
1.3%
7347
 
0.9%
8286
 
0.7%
9148
 
0.4%
ValueCountFrequency (%)
631
 
< 0.1%
561
 
< 0.1%
551
 
< 0.1%
503
< 0.1%
472
< 0.1%
462
< 0.1%
432
< 0.1%
422
< 0.1%
392
< 0.1%
381
 
< 0.1%

Magnesium
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct43
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.428376636
Minimum0
Maximum80
Zeros4931
Zeros (%)12.2%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:37.408414image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile6
Maximum80
Range80
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.489572054
Coefficient of variation (CV)1.025200134
Kurtosis56.87257196
Mean2.428376636
Median Absolute Deviation (MAD)1
Skewness4.765065458
Sum97951
Variance6.197969012
MonotonicityNot monotonic
2021-11-29T11:26:37.576645image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
211109
27.5%
110295
25.5%
36022
14.9%
04931
12.2%
43546
 
8.8%
51421
 
3.5%
61189
 
2.9%
8463
 
1.1%
7419
 
1.0%
10222
 
0.6%
Other values (33)719
 
1.8%
ValueCountFrequency (%)
04931
12.2%
110295
25.5%
211109
27.5%
36022
14.9%
43546
 
8.8%
51421
 
3.5%
61189
 
2.9%
7419
 
1.0%
8463
 
1.1%
9202
 
0.5%
ValueCountFrequency (%)
801
 
< 0.1%
441
 
< 0.1%
422
< 0.1%
402
< 0.1%
393
< 0.1%
381
 
< 0.1%
372
< 0.1%
361
 
< 0.1%
351
 
< 0.1%
331
 
< 0.1%

Phosphate
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct29
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.544550774
Minimum0
Maximum76
Zeros12015
Zeros (%)29.8%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:37.671721image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum76
Range76
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.827234583
Coefficient of variation (CV)1.183020082
Kurtosis89.51114998
Mean1.544550774
Median Absolute Deviation (MAD)1
Skewness4.799045502
Sum62301
Variance3.338786222
MonotonicityNot monotonic
2021-11-29T11:26:37.751344image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
012015
29.8%
111505
28.5%
29130
22.6%
34132
 
10.2%
41651
 
4.1%
5745
 
1.8%
6410
 
1.0%
7228
 
0.6%
8146
 
0.4%
996
 
0.2%
Other values (19)278
 
0.7%
ValueCountFrequency (%)
012015
29.8%
111505
28.5%
29130
22.6%
34132
 
10.2%
41651
 
4.1%
5745
 
1.8%
6410
 
1.0%
7228
 
0.6%
8146
 
0.4%
996
 
0.2%
ValueCountFrequency (%)
761
 
< 0.1%
311
 
< 0.1%
281
 
< 0.1%
264
 
< 0.1%
251
 
< 0.1%
232
 
< 0.1%
223
 
< 0.1%
212
 
< 0.1%
203
 
< 0.1%
1910
< 0.1%

Potassium
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct57
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.583027568
Minimum0
Maximum81
Zeros1867
Zeros (%)4.6%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:37.847971image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile10
Maximum81
Range81
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.651856928
Coefficient of variation (CV)1.019209833
Kurtosis42.11227847
Mean3.583027568
Median Absolute Deviation (MAD)1
Skewness4.451051989
Sum144525
Variance13.33605902
MonotonicityNot monotonic
2021-11-29T11:26:37.948861image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29983
24.7%
17869
19.5%
36601
16.4%
44314
10.7%
52540
 
6.3%
61949
 
4.8%
01867
 
4.6%
71261
 
3.1%
81058
 
2.6%
9659
 
1.6%
Other values (47)2235
 
5.5%
ValueCountFrequency (%)
01867
 
4.6%
17869
19.5%
29983
24.7%
36601
16.4%
44314
10.7%
52540
 
6.3%
61949
 
4.8%
71261
 
3.1%
81058
 
2.6%
9659
 
1.6%
ValueCountFrequency (%)
811
 
< 0.1%
771
 
< 0.1%
761
 
< 0.1%
661
 
< 0.1%
611
 
< 0.1%
592
< 0.1%
523
< 0.1%
513
< 0.1%
491
 
< 0.1%
481
 
< 0.1%

Bilirubin_total
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct24
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5737058707
Minimum0
Maximum73
Zeros26088
Zeros (%)64.7%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:38.043991image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum73
Range73
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.147170566
Coefficient of variation (CV)1.999579619
Kurtosis436.3002398
Mean0.5737058707
Median Absolute Deviation (MAD)0
Skewness10.30497772
Sum23141
Variance1.316000309
MonotonicityNot monotonic
2021-11-29T11:26:38.122736image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
026088
64.7%
19289
 
23.0%
23143
 
7.8%
31026
 
2.5%
4344
 
0.9%
5174
 
0.4%
6106
 
0.3%
768
 
0.2%
830
 
0.1%
915
 
< 0.1%
Other values (14)53
 
0.1%
ValueCountFrequency (%)
026088
64.7%
19289
 
23.0%
23143
 
7.8%
31026
 
2.5%
4344
 
0.9%
5174
 
0.4%
6106
 
0.3%
768
 
0.2%
830
 
0.1%
915
 
< 0.1%
ValueCountFrequency (%)
731
 
< 0.1%
301
 
< 0.1%
261
 
< 0.1%
231
 
< 0.1%
211
 
< 0.1%
181
 
< 0.1%
171
 
< 0.1%
162
< 0.1%
153
< 0.1%
144
< 0.1%

TroponinI
Real number (ℝ≥0)

ZEROS

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3664468465
Minimum0
Maximum17
Zeros33283
Zeros (%)82.5%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:38.204383image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum17
Range17
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.00471862
Coefficient of variation (CV)2.741785418
Kurtosis20.67235827
Mean0.3664468465
Median Absolute Deviation (MAD)0
Skewness3.896794737
Sum14781
Variance1.009459506
MonotonicityNot monotonic
2021-11-29T11:26:38.275529image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
033283
82.5%
13261
 
8.1%
21841
 
4.6%
3965
 
2.4%
4488
 
1.2%
5246
 
0.6%
6120
 
0.3%
778
 
0.2%
828
 
0.1%
914
 
< 0.1%
Other values (5)12
 
< 0.1%
ValueCountFrequency (%)
033283
82.5%
13261
 
8.1%
21841
 
4.6%
3965
 
2.4%
4488
 
1.2%
5246
 
0.6%
6120
 
0.3%
778
 
0.2%
828
 
0.1%
914
 
< 0.1%
ValueCountFrequency (%)
171
 
< 0.1%
142
 
< 0.1%
123
 
< 0.1%
114
 
< 0.1%
102
 
< 0.1%
914
 
< 0.1%
828
 
0.1%
778
 
0.2%
6120
0.3%
5246
0.6%

Hct
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct53
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.407204482
Minimum0
Maximum114
Zeros2317
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:38.367132image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile10
Maximum114
Range114
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.443034322
Coefficient of variation (CV)1.010515905
Kurtosis49.85236302
Mean3.407204482
Median Absolute Deviation (MAD)1
Skewness4.19296479
Sum137433
Variance11.85448534
MonotonicityNot monotonic
2021-11-29T11:26:38.466098image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
210174
25.2%
18733
21.7%
35924
14.7%
43746
 
9.3%
52514
 
6.2%
02317
 
5.7%
61999
 
5.0%
71260
 
3.1%
8982
 
2.4%
9651
 
1.6%
Other values (43)2036
 
5.0%
ValueCountFrequency (%)
02317
 
5.7%
18733
21.7%
210174
25.2%
35924
14.7%
43746
 
9.3%
52514
 
6.2%
61999
 
5.0%
71260
 
3.1%
8982
 
2.4%
9651
 
1.6%
ValueCountFrequency (%)
1141
< 0.1%
611
< 0.1%
601
< 0.1%
591
< 0.1%
491
< 0.1%
481
< 0.1%
472
< 0.1%
462
< 0.1%
442
< 0.1%
431
< 0.1%

Hgb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct42
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.840911345
Minimum0
Maximum102
Zeros2448
Zeros (%)6.1%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:38.566560image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile8
Maximum102
Range102
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.699852978
Coefficient of variation (CV)0.9503474942
Kurtosis68.46219899
Mean2.840911345
Median Absolute Deviation (MAD)1
Skewness4.569285511
Sum114591
Variance7.289206101
MonotonicityNot monotonic
2021-11-29T11:26:38.657226image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
211760
29.2%
19822
24.4%
36339
15.7%
43541
 
8.8%
02448
 
6.1%
51939
 
4.8%
61501
 
3.7%
7835
 
2.1%
8668
 
1.7%
9429
 
1.1%
Other values (32)1054
 
2.6%
ValueCountFrequency (%)
02448
 
6.1%
19822
24.4%
211760
29.2%
36339
15.7%
43541
 
8.8%
51939
 
4.8%
61501
 
3.7%
7835
 
2.1%
8668
 
1.7%
9429
 
1.1%
ValueCountFrequency (%)
1021
 
< 0.1%
531
 
< 0.1%
441
 
< 0.1%
411
 
< 0.1%
381
 
< 0.1%
373
< 0.1%
351
 
< 0.1%
344
< 0.1%
335
< 0.1%
321
 
< 0.1%

PTT
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct34
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.132958152
Minimum0
Maximum105
Zeros20098
Zeros (%)49.8%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:38.747268image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum105
Range105
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.913979714
Coefficient of variation (CV)1.689364882
Kurtosis247.8086848
Mean1.132958152
Median Absolute Deviation (MAD)1
Skewness7.737430076
Sum45699
Variance3.663318345
MonotonicityNot monotonic
2021-11-29T11:26:38.834500image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
020098
49.8%
19541
23.7%
25069
 
12.6%
32421
 
6.0%
41238
 
3.1%
5787
 
2.0%
6440
 
1.1%
7279
 
0.7%
8148
 
0.4%
990
 
0.2%
Other values (24)225
 
0.6%
ValueCountFrequency (%)
020098
49.8%
19541
23.7%
25069
 
12.6%
32421
 
6.0%
41238
 
3.1%
5787
 
2.0%
6440
 
1.1%
7279
 
0.7%
8148
 
0.4%
990
 
0.2%
ValueCountFrequency (%)
1051
 
< 0.1%
441
 
< 0.1%
351
 
< 0.1%
311
 
< 0.1%
301
 
< 0.1%
294
< 0.1%
281
 
< 0.1%
271
 
< 0.1%
261
 
< 0.1%
242
< 0.1%

WBC
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct39
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.465465093
Minimum0
Maximum83
Zeros2625
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:38.928082image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile6
Maximum83
Range83
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.233798842
Coefficient of variation (CV)0.9060354772
Kurtosis73.98345613
Mean2.465465093
Median Absolute Deviation (MAD)1
Skewness4.973686524
Sum99447
Variance4.989857267
MonotonicityNot monotonic
2021-11-29T11:26:39.087864image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
213103
32.5%
110741
26.6%
36467
16.0%
43249
 
8.1%
02625
 
6.5%
51385
 
3.4%
61088
 
2.7%
7439
 
1.1%
8412
 
1.0%
9229
 
0.6%
Other values (29)598
 
1.5%
ValueCountFrequency (%)
02625
 
6.5%
110741
26.6%
213103
32.5%
36467
16.0%
43249
 
8.1%
51385
 
3.4%
61088
 
2.7%
7439
 
1.1%
8412
 
1.0%
9229
 
0.6%
ValueCountFrequency (%)
831
< 0.1%
521
< 0.1%
372
< 0.1%
351
< 0.1%
341
< 0.1%
332
< 0.1%
321
< 0.1%
312
< 0.1%
302
< 0.1%
292
< 0.1%

Fibrinogen
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct29
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2539170964
Minimum0
Maximum90
Zeros35821
Zeros (%)88.8%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:39.172459image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum90
Range90
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.164592512
Coefficient of variation (CV)4.586506889
Kurtosis977.6917743
Mean0.2539170964
Median Absolute Deviation (MAD)0
Skewness18.69767076
Sum10242
Variance1.356275718
MonotonicityNot monotonic
2021-11-29T11:26:39.252976image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
035821
88.8%
12477
 
6.1%
2929
 
2.3%
3371
 
0.9%
4260
 
0.6%
5134
 
0.3%
6126
 
0.3%
766
 
0.2%
845
 
0.1%
921
 
0.1%
Other values (19)86
 
0.2%
ValueCountFrequency (%)
035821
88.8%
12477
 
6.1%
2929
 
2.3%
3371
 
0.9%
4260
 
0.6%
5134
 
0.3%
6126
 
0.3%
766
 
0.2%
845
 
0.1%
921
 
0.1%
ValueCountFrequency (%)
901
 
< 0.1%
321
 
< 0.1%
301
 
< 0.1%
291
 
< 0.1%
281
 
< 0.1%
242
< 0.1%
231
 
< 0.1%
221
 
< 0.1%
211
 
< 0.1%
194
< 0.1%

Platelets
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct35
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.286022412
Minimum0
Maximum109
Zeros2577
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:39.340930image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum109
Range109
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.949893974
Coefficient of variation (CV)0.8529636299
Kurtosis246.8492044
Mean2.286022412
Median Absolute Deviation (MAD)1
Skewness7.33286181
Sum92209
Variance3.802086511
MonotonicityNot monotonic
2021-11-29T11:26:39.429078image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
213508
33.5%
111356
28.2%
37005
17.4%
42810
 
7.0%
02577
 
6.4%
51231
 
3.1%
6677
 
1.7%
7364
 
0.9%
8251
 
0.6%
9163
 
0.4%
Other values (25)394
 
1.0%
ValueCountFrequency (%)
02577
 
6.4%
111356
28.2%
213508
33.5%
37005
17.4%
42810
 
7.0%
51231
 
3.1%
6677
 
1.7%
7364
 
0.9%
8251
 
0.6%
9163
 
0.4%
ValueCountFrequency (%)
1091
< 0.1%
351
< 0.1%
331
< 0.1%
321
< 0.1%
312
< 0.1%
301
< 0.1%
282
< 0.1%
271
< 0.1%
262
< 0.1%
252
< 0.1%

Age
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct273
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.48200119
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:39.523994image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile14
Q124
median38
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)23

Descriptive statistics

Standard deviation22.79592332
Coefficient of variation (CV)0.5923788425
Kurtosis42.42147962
Mean38.48200119
Median Absolute Deviation (MAD)11
Skewness4.840449261
Sum1552210
Variance519.6541201
MonotonicityNot monotonic
2021-11-29T11:26:39.623628image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
361364
 
3.4%
391362
 
3.4%
381323
 
3.3%
401285
 
3.2%
411271
 
3.2%
371223
 
3.0%
431210
 
3.0%
421193
 
3.0%
441143
 
2.8%
451089
 
2.7%
Other values (263)27873
69.1%
ValueCountFrequency (%)
8328
0.8%
9236
 
0.6%
10221
 
0.5%
11234
 
0.6%
12285
 
0.7%
13350
0.9%
14412
1.0%
15536
1.3%
16601
1.5%
17721
1.8%
ValueCountFrequency (%)
33610
< 0.1%
3353
 
< 0.1%
3342
 
< 0.1%
3331
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3271
 
< 0.1%
3261
 
< 0.1%
3201
 
< 0.1%
3181
 
< 0.1%

Gender
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct273
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.48200119
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:39.728352image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile14
Q124
median38
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)23

Descriptive statistics

Standard deviation22.79592332
Coefficient of variation (CV)0.5923788425
Kurtosis42.42147962
Mean38.48200119
Median Absolute Deviation (MAD)11
Skewness4.840449261
Sum1552210
Variance519.6541201
MonotonicityNot monotonic
2021-11-29T11:26:39.826435image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
361364
 
3.4%
391362
 
3.4%
381323
 
3.3%
401285
 
3.2%
411271
 
3.2%
371223
 
3.0%
431210
 
3.0%
421193
 
3.0%
441143
 
2.8%
451089
 
2.7%
Other values (263)27873
69.1%
ValueCountFrequency (%)
8328
0.8%
9236
 
0.6%
10221
 
0.5%
11234
 
0.6%
12285
 
0.7%
13350
0.9%
14412
1.0%
15536
1.3%
16601
1.5%
17721
1.8%
ValueCountFrequency (%)
33610
< 0.1%
3353
 
< 0.1%
3342
 
< 0.1%
3331
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3271
 
< 0.1%
3261
 
< 0.1%
3201
 
< 0.1%
3181
 
< 0.1%

Unit1
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct234
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.31044228
Minimum0
Maximum336
Zeros15617
Zeros (%)38.7%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:39.930796image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median21
Q341
95-th percentile55
Maximum336
Range336
Interquartile range (IQR)41

Descriptive statistics

Standard deviation25.09279698
Coefficient of variation (CV)1.076461642
Kurtosis19.06781227
Mean23.31044228
Median Absolute Deviation (MAD)21
Skewness2.520636771
Sum940250
Variance629.6484602
MonotonicityNot monotonic
2021-11-29T11:26:40.029274image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
015617
38.7%
36847
 
2.1%
39827
 
2.1%
41806
 
2.0%
40789
 
2.0%
38770
 
1.9%
43763
 
1.9%
37753
 
1.9%
42729
 
1.8%
44696
 
1.7%
Other values (224)17739
44.0%
ValueCountFrequency (%)
015617
38.7%
8215
 
0.5%
9137
 
0.3%
10136
 
0.3%
11125
 
0.3%
12159
 
0.4%
13196
 
0.5%
14236
 
0.6%
15309
 
0.8%
16356
 
0.9%
ValueCountFrequency (%)
3364
< 0.1%
3352
< 0.1%
3341
 
< 0.1%
3331
 
< 0.1%
3271
 
< 0.1%
3261
 
< 0.1%
3201
 
< 0.1%
3102
< 0.1%
3071
 
< 0.1%
3001
 
< 0.1%

Unit2
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct234
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.31044228
Minimum0
Maximum336
Zeros15617
Zeros (%)38.7%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:40.134298image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median21
Q341
95-th percentile55
Maximum336
Range336
Interquartile range (IQR)41

Descriptive statistics

Standard deviation25.09279698
Coefficient of variation (CV)1.076461642
Kurtosis19.06781227
Mean23.31044228
Median Absolute Deviation (MAD)21
Skewness2.520636771
Sum940250
Variance629.6484602
MonotonicityNot monotonic
2021-11-29T11:26:40.233056image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
015617
38.7%
36847
 
2.1%
39827
 
2.1%
41806
 
2.0%
40789
 
2.0%
38770
 
1.9%
43763
 
1.9%
37753
 
1.9%
42729
 
1.8%
44696
 
1.7%
Other values (224)17739
44.0%
ValueCountFrequency (%)
015617
38.7%
8215
 
0.5%
9137
 
0.3%
10136
 
0.3%
11125
 
0.3%
12159
 
0.4%
13196
 
0.5%
14236
 
0.6%
15309
 
0.8%
16356
 
0.9%
ValueCountFrequency (%)
3364
< 0.1%
3352
< 0.1%
3341
 
< 0.1%
3331
 
< 0.1%
3271
 
< 0.1%
3261
 
< 0.1%
3201
 
< 0.1%
3102
< 0.1%
3071
 
< 0.1%
3001
 
< 0.1%

HospAdmTime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct274
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.48180286
Minimum0
Maximum336
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:40.337826image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14
Q124
median38
Q347
95-th percentile58
Maximum336
Range336
Interquartile range (IQR)23

Descriptive statistics

Standard deviation22.79622333
Coefficient of variation (CV)0.5923896918
Kurtosis42.41937911
Mean38.48180286
Median Absolute Deviation (MAD)11
Skewness4.840224264
Sum1552202
Variance519.6677983
MonotonicityNot monotonic
2021-11-29T11:26:40.510002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
361364
 
3.4%
391362
 
3.4%
381323
 
3.3%
401285
 
3.2%
411271
 
3.2%
371223
 
3.0%
431210
 
3.0%
421193
 
3.0%
441143
 
2.8%
451089
 
2.7%
Other values (264)27873
69.1%
ValueCountFrequency (%)
01
 
< 0.1%
8327
0.8%
9236
 
0.6%
10221
 
0.5%
11234
 
0.6%
12285
0.7%
13350
0.9%
14412
1.0%
15536
1.3%
16601
1.5%
ValueCountFrequency (%)
33610
< 0.1%
3353
 
< 0.1%
3342
 
< 0.1%
3331
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3271
 
< 0.1%
3261
 
< 0.1%
3201
 
< 0.1%
3181
 
< 0.1%

ICULOS
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct273
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.48200119
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:40.614413image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile14
Q124
median38
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)23

Descriptive statistics

Standard deviation22.79592332
Coefficient of variation (CV)0.5923788425
Kurtosis42.42147962
Mean38.48200119
Median Absolute Deviation (MAD)11
Skewness4.840449261
Sum1552210
Variance519.6541201
MonotonicityNot monotonic
2021-11-29T11:26:40.712669image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
361364
 
3.4%
391362
 
3.4%
381323
 
3.3%
401285
 
3.2%
411271
 
3.2%
371223
 
3.0%
431210
 
3.0%
421193
 
3.0%
441143
 
2.8%
451089
 
2.7%
Other values (263)27873
69.1%
ValueCountFrequency (%)
8328
0.8%
9236
 
0.6%
10221
 
0.5%
11234
 
0.6%
12285
 
0.7%
13350
0.9%
14412
1.0%
15536
1.3%
16601
1.5%
17721
1.8%
ValueCountFrequency (%)
33610
< 0.1%
3353
 
< 0.1%
3342
 
< 0.1%
3331
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3271
 
< 0.1%
3261
 
< 0.1%
3201
 
< 0.1%
3181
 
< 0.1%

SepsisLabel
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct273
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.48200119
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:40.818992image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile14
Q124
median38
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)23

Descriptive statistics

Standard deviation22.79592332
Coefficient of variation (CV)0.5923788425
Kurtosis42.42147962
Mean38.48200119
Median Absolute Deviation (MAD)11
Skewness4.840449261
Sum1552210
Variance519.6541201
MonotonicityNot monotonic
2021-11-29T11:26:40.917095image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
361364
 
3.4%
391362
 
3.4%
381323
 
3.3%
401285
 
3.2%
411271
 
3.2%
371223
 
3.0%
431210
 
3.0%
421193
 
3.0%
441143
 
2.8%
451089
 
2.7%
Other values (263)27873
69.1%
ValueCountFrequency (%)
8328
0.8%
9236
 
0.6%
10221
 
0.5%
11234
 
0.6%
12285
 
0.7%
13350
0.9%
14412
1.0%
15536
1.3%
16601
1.5%
17721
1.8%
ValueCountFrequency (%)
33610
< 0.1%
3353
 
< 0.1%
3342
 
< 0.1%
3331
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3271
 
< 0.1%
3261
 
< 0.1%
3201
 
< 0.1%
3181
 
< 0.1%

Sepsis
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct273
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.48200119
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:41.022128image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile14
Q124
median38
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)23

Descriptive statistics

Standard deviation22.79592332
Coefficient of variation (CV)0.5923788425
Kurtosis42.42147962
Mean38.48200119
Median Absolute Deviation (MAD)11
Skewness4.840449261
Sum1552210
Variance519.6541201
MonotonicityNot monotonic
2021-11-29T11:26:41.120434image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
361364
 
3.4%
391362
 
3.4%
381323
 
3.3%
401285
 
3.2%
411271
 
3.2%
371223
 
3.0%
431210
 
3.0%
421193
 
3.0%
441143
 
2.8%
451089
 
2.7%
Other values (263)27873
69.1%
ValueCountFrequency (%)
8328
0.8%
9236
 
0.6%
10221
 
0.5%
11234
 
0.6%
12285
 
0.7%
13350
0.9%
14412
1.0%
15536
1.3%
16601
1.5%
17721
1.8%
ValueCountFrequency (%)
33610
< 0.1%
3353
 
< 0.1%
3342
 
< 0.1%
3331
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3271
 
< 0.1%
3261
 
< 0.1%
3201
 
< 0.1%
3181
 
< 0.1%

Hours
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct273
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.48200119
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:26:41.226801image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile14
Q124
median38
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)23

Descriptive statistics

Standard deviation22.79592332
Coefficient of variation (CV)0.5923788425
Kurtosis42.42147962
Mean38.48200119
Median Absolute Deviation (MAD)11
Skewness4.840449261
Sum1552210
Variance519.6541201
MonotonicityNot monotonic
2021-11-29T11:26:41.325468image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
361364
 
3.4%
391362
 
3.4%
381323
 
3.3%
401285
 
3.2%
411271
 
3.2%
371223
 
3.0%
431210
 
3.0%
421193
 
3.0%
441143
 
2.8%
451089
 
2.7%
Other values (263)27873
69.1%
ValueCountFrequency (%)
8328
0.8%
9236
 
0.6%
10221
 
0.5%
11234
 
0.6%
12285
 
0.7%
13350
0.9%
14412
1.0%
15536
1.3%
16601
1.5%
17721
1.8%
ValueCountFrequency (%)
33610
< 0.1%
3353
 
< 0.1%
3342
 
< 0.1%
3331
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3271
 
< 0.1%
3261
 
< 0.1%
3201
 
< 0.1%
3181
 
< 0.1%

Interactions

2021-11-29T11:26:30.797625image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:18.525275image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:18.810188image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:19.082703image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:19.357093image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:19.624397image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:19.968300image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:20.241501image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:20.514406image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:20.788802image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:21.061592image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:21.330460image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:21.589051image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:21.860932image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:22.204082image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:22.470036image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:22.728912image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:23.004805image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:23.287230image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:23.567681image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:23.847625image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:24.198858image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:24.483939image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:24.761029image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:25.048409image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:25.321302image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:25.609092image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:25.888661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:26.173246image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:26.528981image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:26.814902image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:27.081457image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:27.346824image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:27.611726image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:27.870484image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:28.131664image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:28.475395image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:28.754164image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:29.035258image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:29.315530image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:29.596527image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:29.880572image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:30.160960image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:30.444095image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:30.892002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:18.620694image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:18.901729image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:19.174799image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:19.446998image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:19.716437image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:20.059968image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:20.333280image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:20.606669image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:20.880307image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:21.151611image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:21.417241image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:21.680882image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:21.951424image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:22.293519image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:22.556907image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:22.821501image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:23.099743image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:23.381195image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:23.661138image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:23.940910image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:24.294430image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:24.577023image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:24.857445image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:25.139875image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:25.418143image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:25.703048image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:25.984301image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:26.342272image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:26.625025image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:26.904176image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:27.170834image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:27.435936image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:27.699039image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:27.958107image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:28.222534image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:28.568936image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:28.848471image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:29.129537image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:29.409824image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:29.691936image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:29.974709image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:30.256196image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:30.611323image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:30.985351image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:18.715159image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:18.992248image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:19.265940image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:19.535763image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:19.807177image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:20.150707image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:20.424011image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:20.698278image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:20.970871image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:21.241232image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:21.503152image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:21.771252image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:22.114608image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:22.381968image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:22.642816image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:22.913057image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:23.194362image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:23.474302image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:23.755246image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:24.033319image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:24.389420image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:24.668308image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:24.952853image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:25.230509image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:25.513890image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:25.795961image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:26.079172image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:26.435658image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:26.719963image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:26.993033image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:27.259092image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:27.523802image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:27.785239image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:28.044792image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:28.312700image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:28.661425image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:28.942275image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:29.222705image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:29.503434image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:29.786318image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:30.068015image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:30.350135image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:26:30.704450image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2021-11-29T11:26:41.468969image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-11-29T11:26:41.802936image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-11-29T11:26:42.209682image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Missing values

2021-11-29T11:26:31.225101image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
A simple visualization of nullity by column.
2021-11-29T11:26:32.313359image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

PatientIDHRO2SatTempSBPMAPDBPRespEtCO2BaseExcessHCO3FiO2pHPaCO2SaO2ASTBUNAlkalinephosCalciumChlorideCreatinineBilirubin_directGlucoseLactateMagnesiumPhosphatePotassiumBilirubin_totalTroponinIHctHgbPTTWBCFibrinogenPlateletsAgeGenderUnit1Unit2HospAdmTimeICULOSSepsisLabelSepsisHours
0149441042420500724764121222020222102202025454005454545454
122222615221519001000001011101011100110101232323232323232323
2345441645454245023732003033303033400432303484848484848484848
342727626261426022032302012203021300212102292929292929292929
45242192417021003000033333303033330332303484848484848484848
5616165151506011211001001103100100110101171717171717171717
67444414444443440561355016166606266610655506454545454545454545
783836113838383801411014800110411607107412006606034040004040404040
892382381122382382252380472177474712019017191903624181835003327141761925825800258258258258258
91023232123232323042744302003203110300321202232323232323232323

Last rows

PatientIDHRO2SatTempSBPMAPDBPRespEtCO2BaseExcessHCO3FiO2pHPaCO2SaO2ASTBUNAlkalinephosCalciumChlorideCreatinineBilirubin_directGlucoseLactateMagnesiumPhosphatePotassiumBilirubin_totalTroponinIHctHgbPTTWBCFibrinogenPlateletsAgeGenderUnit1Unit2HospAdmTimeICULOSSepsisLabelSepsisHours
40326119991232223232323193000000010101011010100110101252525252525252525
4032711999240401140404039000000001010106011101110101414141414141414141
4032811999377663680000000010101010111021101012121002121212121
40329119994414141414141409005666030703024631800220202424242424242424242
4033011999541411041414141000000001010107011100110111424242424242424242
40331119996464610454445340000000121202020202121101014848004848484848
4033211999724243242424131000000121202120212112212022525002525252525
4033311999842431238383838000000012120202011210370303494949494949494949
403341199991818518181818000000022220202000220330202202020202020202020
40335120000333373333333100000001212021100112102212023535003535353535